Generative Artificial Intelligence in Education: From Deceptive to Disruptive

被引:21
|
作者
Alier, Marc [1 ]
Garcia-Penalvo, Francisco Jose [2 ]
Camba, Jorge D. [3 ]
机构
[1] Univ Politecn Cataluna, Barcelona, Spain
[2] Univ Salamanca, Res Inst Educ Sci, Salamanca, Spain
[3] Purdue Univ, Purdue, IN 47907 USA
关键词
Artificial Intelligence; Ethical Implications; Ethical Principles; Generative Artificial Intelligence; Large Language Model;
D O I
10.9781/ijimai.2024.02.011
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Generative Artificial Intelligence (GenAI) has emerged as a promising technology that can create original content, such as text, images, and sound. The use of GenAI in educational settings is becoming increasingly popular and offers a range of opportunities and challenges. This special issue explores the management and integration of GenAI in educational settings, including the ethical considerations, best practices, and opportunities. The potential of GenAI in education is vast. By using algorithms and data, GenAI can create original content that can be used to augment traditional teaching methods, creating a more interactive and personalized learning experience. In addition, GenAI can be utilized as an assessment tool and for providing feedback to students using generated content. For instance, it can be used to create custom quizzes, generate essay prompts, or even grade essays. The use of GenAI as an assessment tool can reduce the workload of teachers and help students receive prompt feedback on their work. Incorporating GenAI in educational settings also poses challenges related to academic integrity. With availability of GenAI models, students can use them to study or complete their homework assignments, which can raise concerns about the authenticity and authorship of the delivered work. Therefore, it is important to ensure that academic standards are maintained, and the originality of the student's work is preserved. This issue highlights the need for implementing ethical practices in the use of GenAI models and ensuring that the technology is used to support and not replace the student's learning experience.
引用
收藏
页码:5 / 14
页数:83
相关论文
共 50 条
  • [1] Artificial Intelligence as a Disruptive Technology in Education
    Zovko, Vatroslav
    Gudlin, Monika
    9TH INTERNATIONAL CONFERENCE THE FUTURE OF EDUCATION, 2019, : 141 - 148
  • [2] The Disruptive Impacts of Next Generation Generative Artificial Intelligence
    Byrne, Matthew
    CIN-COMPUTERS INFORMATICS NURSING, 2023, 41 (07) : 479 - 481
  • [3] Generative artificial intelligence and engineering education
    Johri, Aditya
    Katz, Andrew S.
    Qadir, Junaid
    Hingle, Ashish
    JOURNAL OF ENGINEERING EDUCATION, 2023, 112 (03) : 572 - 577
  • [4] Generative Artificial Intelligence and the Education Sector
    Ahmad, Norita
    Murugesan, San
    Kshetri, Nir
    COMPUTER, 2023, 56 (06) : 72 - 76
  • [5] DISRUPTIVE TECHNOLOGIES - ARTIFICIAL INTELLIGENCE AND BLOCKCHAIN IN EDUCATION
    Jekov, B.
    Petkova, P.
    Parusheva, Y.
    Shoikova, E.
    11TH INTERNATIONAL CONFERENCE OF EDUCATION, RESEARCH AND INNOVATION (ICERI2018), 2018, : 6784 - 6793
  • [6] Generative Artificial Intelligence and Education: An Analysis from Multiple Perspectives
    Garcia-Penalvo, Francisco Jose
    EDUCATION IN THE KNOWLEDGE SOCIETY, 2024, 25
  • [7] USING GENERATIVE ARTIFICIAL INTELLIGENCE IN INCLUSIVE EDUCATION
    Arnold, K.
    Chew, S.
    JOURNAL OF INTELLECTUAL DISABILITY RESEARCH, 2024, 68 (07) : 651 - 651
  • [8] Using Generative Artificial Intelligence in Medical Education
    Rodman, Adam
    Mark, Nicholas M.
    Artino, Anthony R.
    Lessing, Juan N.
    ACADEMIC MEDICINE, 2025, 100 (02) : 250 - 250
  • [9] Harnessing Generative Artificial Intelligence for Medical Education
    Lie, Margaret
    Rodman, Adam
    Crowe, Byron
    ACADEMIC MEDICINE, 2025, 100 (01) : 116 - 116
  • [10] Generative artificial intelligence in graduate medical education
    Janumpally, Ravi
    Nanua, Suparna
    Ngo, Andy
    Youens, Kenneth
    FRONTIERS IN MEDICINE, 2025, 11